Clarification: Predicting Large-Scale Hyperparameters from Cheap Small-Scale Sweeps
AlexShtf · x · 2026-08-19
AlexShtf reiterates that interpreting "easier to tune" as "predictable from lower scales" is incorrect. JJitsev clarifies that with sufficient small-scale tuning (cheap), there is a good outlook for accurate large-scale hyperparameter prediction, as the hyperparameter loss surface becomes lower dimensional with increased scale.
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